[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-trail-of-bits-last30days":3,"mdc-mf2qty-key":34,"related-repo-trail-of-bits-last30days":1947,"related-org-trail-of-bits-last30days":2052},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":32,"mdContent":33},"last30days","research recent community discussions and trends","Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"trail-of-bits","Trail of Bits","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Ftrail-of-bits.png","trailofbits",[13,17,20],{"name":14,"slug":15,"type":16},"Research","research","tag",{"name":18,"slug":19,"type":16},"Analysis","analysis",{"name":21,"slug":22,"type":16},"Social Media","social-media",460,"https:\u002F\u002Fgithub.com\u002Ftrailofbits\u002Fskills-curated","2026-07-17T06:04:39.744471",null,29,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":31},[],"Curated, community-vetted Claude Code plugin marketplace","https:\u002F\u002Fgithub.com\u002Ftrailofbits\u002Fskills-curated\u002Ftree\u002FHEAD\u002Fplugins\u002Flast30days\u002Fskills\u002Flast30days","---\nname: last30days\ndescription: \"Researches a topic from the last 30 days on Reddit, X, and the web. Surfaces real community discussions with engagement metrics and synthesizes findings into actionable insights. Use when the user wants to know what people are saying about a topic right now.\"\nargument-hint: 'nano banana pro prompts, NVIDIA news, best AI video tools'\nallowed-tools:\n  - Bash\n  - Read\n  - Write\n  - AskUserQuestion\n  - WebSearch\n  - mcp__exa__web_search_exa\n---\n\n# last30days: Research Any Topic from the Last 30 Days\n\nResearch ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.\n\n## When to Use\n\n- User wants to know what people are saying about a topic in the last 30 days\n- User asks for recent community sentiment, recommendations, or trending discussions\n- User wants to research a topic before making a decision (tools, products, techniques)\n- User asks \"what's new with X\" or \"best Y\" or \"what are people saying about Z\"\n\n## When NOT to Use\n\n- User wants historical data older than 30 days\n- User needs official documentation or API references (use docs tools instead)\n- User wants to search a specific codebase (use code search tools)\n- User asks a factual question that doesn't need community sentiment\n\n## CRITICAL: Parse User Intent\n\nBefore doing anything, parse the user's input for:\n\n1. **TOPIC**: What they want to learn about (e.g., \"web app mockups\", \"Claude Code skills\", \"image generation\")\n2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., \"Nano Banana Pro\", \"ChatGPT\", \"Midjourney\")\n3. **QUERY TYPE**: What kind of research they want:\n   - **PROMPTING** - \"X prompts\", \"prompting for X\", \"X best practices\" -> User wants to learn techniques and get copy-paste prompts\n   - **RECOMMENDATIONS** - \"best X\", \"top X\", \"what X should I use\", \"recommended X\" -> User wants a LIST of specific things\n   - **NEWS** - \"what's happening with X\", \"X news\", \"latest on X\" -> User wants current events\u002Fupdates\n   - **GENERAL** - anything else -> User wants broad understanding of the topic\n\nCommon patterns:\n- `[topic] for [tool]` -> \"web mockups for Nano Banana Pro\" -> TOOL IS SPECIFIED\n- `[topic] prompts for [tool]` -> \"UI design prompts for Midjourney\" -> TOOL IS SPECIFIED\n- Just `[topic]` -> \"iOS design mockups\" -> TOOL NOT SPECIFIED, that's OK\n- \"best [topic]\" or \"top [topic]\" -> QUERY_TYPE = RECOMMENDATIONS\n- \"what are the best [topic]\" -> QUERY_TYPE = RECOMMENDATIONS\n\n**IMPORTANT: Do NOT ask about target tool before research.**\n- If tool is specified in the query, use it\n- If tool is NOT specified, run research first, then ask AFTER showing results\n\n**Store these variables:**\n- `TOPIC = [extracted topic]`\n- `TARGET_TOOL = [extracted tool, or \"unknown\" if not specified]`\n- `QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]`\n\n**DISPLAY your parsing to the user.** Before running any tools, output:\n\n```\nI'll research {TOPIC} across Reddit, X, and the web to find what's been discussed in the last 30 days.\n\nParsed intent:\n- TOPIC = {TOPIC}\n- TARGET_TOOL = {TARGET_TOOL or \"unknown\"}\n- QUERY_TYPE = {QUERY_TYPE}\n\nStarting now.\n```\n\nIf TARGET_TOOL is known, mention it in the intro: \"...to find {QUERY_TYPE}-style content for use in {TARGET_TOOL}.\"\n\nThis text MUST appear before you call any tools. It confirms to the user that you understood their request.\n\n---\n\n## Research Execution\n\n**Step 1: Run the research script**\n```bash\npython3 \"{baseDir}\u002Fscripts\u002Flast30days.py\" \"$ARGUMENTS\" --emit=compact 2>&1\n```\n\nThe script will automatically:\n- Detect available API keys\n- Run Reddit\u002FX searches if keys exist\n- Signal if WebSearch is needed\n\n---\n\n## STEP 2: DO WEBSEARCH WHILE SCRIPT RUNS\n\nThe script auto-detects sources (API keys, etc). While waiting for it, do WebSearch.\n\nFor **ALL modes**, do WebSearch to supplement (or provide all data in web-only mode).\n\nChoose search queries based on QUERY_TYPE:\n\n**If RECOMMENDATIONS** (\"best X\", \"top X\", \"what X should I use\"):\n- Search for: `best {TOPIC} recommendations`\n- Search for: `{TOPIC} list examples`\n- Search for: `most popular {TOPIC}`\n- Goal: Find SPECIFIC NAMES of things, not generic advice\n\n**If NEWS** (\"what's happening with X\", \"X news\"):\n- Search for: `{TOPIC} news 2026`\n- Search for: `{TOPIC} announcement update`\n- Goal: Find current events and recent developments\n\n**If PROMPTING** (\"X prompts\", \"prompting for X\"):\n- Search for: `{TOPIC} prompts examples 2026`\n- Search for: `{TOPIC} techniques tips`\n- Goal: Find prompting techniques and examples to create copy-paste prompts\n\n**If GENERAL** (default):\n- Search for: `{TOPIC} 2026`\n- Search for: `{TOPIC} discussion`\n- Goal: Find what people are actually saying\n\nFor ALL query types:\n- **USE THE USER'S EXACT TERMINOLOGY** - don't substitute or add tech names based on your knowledge\n- EXCLUDE reddit.com, x.com, twitter.com (covered by script)\n- INCLUDE: blogs, tutorials, docs, news, GitHub repos\n- **DO NOT output \"Sources:\" list** - this is noise, we'll show stats at the end\n\n**Options** (passed through from user's command):\n- `--days=N` -> Look back N days instead of 30 (e.g., `--days=7` for weekly roundup)\n- `--quick` -> Faster, fewer sources (8-12 each)\n- (default) -> Balanced (20-30 each)\n- `--deep` -> Comprehensive (50-70 Reddit, 40-60 X)\n\n---\n\n## Judge Agent: Synthesize All Sources\n\n**After all searches complete, internally synthesize (don't display stats yet):**\n\nThe Judge Agent must:\n1. Weight Reddit\u002FX sources HIGHER (they have engagement signals: upvotes, likes)\n2. Weight WebSearch sources LOWER (no engagement data)\n3. Identify patterns that appear across ALL three sources (strongest signals)\n4. Note any contradictions between sources\n5. Extract the top 3-5 actionable insights\n\n**Do NOT display stats here - they come at the end, right before the invitation.**\n\n---\n\n## FIRST: Internalize the Research\n\n**CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.**\n\nRead the research output carefully. Pay attention to:\n- **Exact product\u002Ftool names** mentioned (e.g., if research mentions \"ClawdBot\" or \"@clawdbot\", that's a DIFFERENT product than \"Claude Code\" - don't conflate them)\n- **Specific quotes and insights** from the sources - use THESE, not generic knowledge\n- **What the sources actually say**, not what you assume the topic is about\n\n**ANTI-PATTERN TO AVOID**: If user asks about \"clawdbot skills\" and research returns ClawdBot content (self-hosted AI agent), do NOT synthesize this as \"Claude Code skills\" just because both involve \"skills\". Read what the research actually says.\n\n### If QUERY_TYPE = RECOMMENDATIONS\n\n**CRITICAL: Extract SPECIFIC NAMES, not generic patterns.**\n\nWhen user asks \"best X\" or \"top X\", they want a LIST of specific things:\n- Scan research for specific product names, tool names, project names, skill names, etc.\n- Count how many times each is mentioned\n- Note which sources recommend each (Reddit thread, X post, blog)\n- List them by popularity\u002Fmention count\n\n**BAD synthesis for \"best Claude Code skills\":**\n> \"Skills are powerful. Keep them under 500 lines. Use progressive disclosure.\"\n\n**GOOD synthesis for \"best Claude Code skills\":**\n> \"Most mentioned skills: \u002Fcommit (5 mentions), remotion skill (4x), git-worktree (3x), \u002Fpr (3x). The Remotion announcement got 16K likes on X.\"\n\n### For all QUERY_TYPEs\n\nIdentify from the ACTUAL RESEARCH OUTPUT:\n- **PROMPT FORMAT** - Does research recommend JSON, structured params, natural language, keywords?\n- The top 3-5 patterns\u002Ftechniques that appeared across multiple sources\n- Specific keywords, structures, or approaches mentioned BY THE SOURCES\n- Common pitfalls mentioned BY THE SOURCES\n\n---\n\n## THEN: Show Summary + Invite Vision\n\n**Display in this EXACT sequence:**\n\n**FIRST - What I learned (based on QUERY_TYPE):**\n\n**If RECOMMENDATIONS** - Show specific things mentioned with sources:\n```\nMost mentioned:\n\n[Tool Name] - {n}x mentions\nUse Case: [what it does]\nSources: @handle1, @handle2, r\u002Fsub, blog.com\n\n[Tool Name] - {n}x mentions\nUse Case: [what it does]\nSources: @handle3, r\u002Fsub2, Complex\n\nNotable mentions: [other specific things with 1-2 mentions]\n```\n\n**CRITICAL for RECOMMENDATIONS:**\n- Each item MUST have a \"Sources:\" line with actual @handles from X posts (e.g., @LONGLIVE47, @ByDobson)\n- Include subreddit names (r\u002Fhiphopheads) and web sources (Complex, Variety)\n- Parse @handles from research output and include the highest-engagement ones\n- Format naturally - tables work well for wide terminals, stacked cards for narrow\n\n**If PROMPTING\u002FNEWS\u002FGENERAL** - Show synthesis and patterns:\n\nCITATION RULE: Cite sources sparingly to prove research is real.\n- In the \"What I learned\" intro: cite 1-2 top sources total, not every sentence\n- In KEY PATTERNS: cite 1 source per pattern, short format: \"per @handle\" or \"per r\u002Fsub\"\n- Do NOT include engagement metrics in citations (likes, upvotes) - save those for stats box\n- Do NOT chain multiple citations: \"per @x, @y, @z\" is too much. Pick the strongest one.\n\nCITATION PRIORITY (most to least preferred):\n1. @handles from X -- \"per @handle\" (these prove the tool's unique value)\n2. r\u002Fsubreddits from Reddit -- \"per r\u002Fsubreddit\"\n3. Web sources -- ONLY when Reddit\u002FX don't cover that specific fact\n\nThe tool's value is surfacing what PEOPLE are saying, not what journalists wrote.\nWhen both a web article and an X post cover the same fact, cite the X post.\n\nURL FORMATTING: NEVER paste raw URLs in the output.\n- **BAD:** \"per https:\u002F\u002Fwww.rollingstone.com\u002Fmusic\u002Fmusic-news\u002Fkanye-west-bully-1235506094\u002F\"\n- **GOOD:** \"per Rolling Stone\"\n- **GOOD:** \"per Complex\"\nUse the publication name, not the URL. The user doesn't need links -- they need clean, readable text.\n\n**BAD:** \"His album is set for March 20 (per Rolling Stone; Billboard; Complex).\"\n**GOOD:** \"His album BULLY drops March 20 -- fans on X are split on the tracklist, per @honest30bgfan_\"\n**GOOD:** \"Ye's apology got massive traction on r\u002Fhiphopheads\"\n**OK** (web, only when Reddit\u002FX don't have it): \"The Hellwatt Festival runs July 4-18 at RCF Arena, per Billboard\"\n\n**Lead with people, not publications.** Start each topic with what Reddit\u002FX\nusers are saying\u002Ffeeling, then add web context only if needed. The user came\nhere for the conversation, not the press release.\n\n```\nWhat I learned:\n\n**{Topic 1}** -- [1-2 sentences about what people are saying, per @handle or r\u002Fsub]\n\n**{Topic 2}** -- [1-2 sentences, per @handle or r\u002Fsub]\n\n**{Topic 3}** -- [1-2 sentences, per @handle or r\u002Fsub]\n\nKEY PATTERNS from the research:\n1. [Pattern] -- per @handle\n2. [Pattern] -- per r\u002Fsub\n3. [Pattern] -- per @handle\n```\n\n**THEN - Stats (right before invitation):**\n\n**CRITICAL: Calculate actual totals from the research output.**\n- Count posts\u002Fthreads from each section\n- Sum engagement: parse `[Xlikes, Yrt]` from each X post, `[Xpts, Ycmt]` from Reddit\n- Identify top voices: highest-engagement @handles from X, most active subreddits\n\n**Copy this EXACTLY, replacing only the {placeholders}:**\n\n```\n---\nAll agents reported back!\n|- Reddit: {N} threads | {N} upvotes | {N} comments\n|- X: {N} posts | {N} likes | {N} reposts (via xAI)\n|- Web: {N} pages (supplementary)\n|- Top voices: @{handle1} ({N} likes), @{handle2} | r\u002F{sub1}, r\u002F{sub2}\n---\n```\n\nIf Reddit returned 0 threads, write: \"|- Reddit: 0 threads (no results this cycle)\"\n\n**SELF-CHECK before displaying**: Re-read your \"What I learned\" section. Does it match what the research ACTUALLY says? If you catch yourself projecting your own knowledge instead of the research, rewrite it.\n\n**LAST - Invitation (adapt to QUERY_TYPE):**\n\n**CRITICAL: Every invitation MUST include 2-3 specific example suggestions based on what you ACTUALLY learned from the research.** Don't be generic -- show the user you absorbed the content by referencing real things from the results.\n\n**If QUERY_TYPE = PROMPTING:**\n```\n---\nI'm now an expert on {TOPIC} for {TARGET_TOOL}. What do you want to make? For example:\n- [specific idea based on popular technique from research]\n- [specific idea based on trending style\u002Fapproach from research]\n- [specific idea riffing on what people are actually creating]\n\nJust describe your vision and I'll write a prompt you can paste straight into {TARGET_TOOL}.\n```\n\n**If QUERY_TYPE = RECOMMENDATIONS:**\n```\n---\nI'm now an expert on {TOPIC}. Want me to go deeper? For example:\n- [Compare specific item A vs item B from the results]\n- [Explain why item C is trending right now]\n- [Help you get started with item D]\n```\n\n**If QUERY_TYPE = NEWS:**\n```\n---\nI'm now an expert on {TOPIC}. Some things you could ask:\n- [Specific follow-up question about the biggest story]\n- [Question about implications of a key development]\n- [Question about what might happen next based on current trajectory]\n```\n\n**If QUERY_TYPE = GENERAL:**\n```\n---\nI'm now an expert on {TOPIC}. Some things I can help with:\n- [Specific question based on the most discussed aspect]\n- [Specific creative\u002Fpractical application of what you learned]\n- [Deeper dive into a pattern or debate from the research]\n```\n\n**Example invitations (to show the quality bar):**\n\nFor `\u002Flast30days nano banana pro prompts for Gemini`:\n> I'm now an expert on Nano Banana Pro for Gemini. What do you want to make? For example:\n> - Photorealistic product shots with natural lighting (the most requested style right now)\n> - Logo designs with embedded text (Gemini's new strength per the research)\n> - Multi-reference style transfer from a mood board\n>\n> Just describe your vision and I'll write a prompt you can paste straight into Gemini.\n\nFor `\u002Flast30days kanye west` (GENERAL):\n> I'm now an expert on Kanye West. Some things I can help with:\n> - What's the real story behind the apology letter -- genuine or PR move?\n> - Break down the BULLY tracklist reactions and what fans are expecting\n> - Compare how Reddit vs X are reacting to the Bianca narrative\n\nFor `\u002Flast30days war in Iran` (NEWS):\n> I'm now an expert on the Iran situation. Some things you could ask:\n> - What are the realistic escalation scenarios from here?\n> - How is this playing differently in US vs international media?\n> - What's the economic impact on oil markets so far?\n\n---\n\n## WAIT FOR USER'S RESPONSE\n\nAfter showing the stats summary with your invitation, **STOP and wait** for the user to respond.\n\n---\n\n## WHEN USER RESPONDS\n\n**Read their response and match the intent:**\n\n- If they ask a **QUESTION** about the topic -> Answer from your research (no new searches, no prompt)\n- If they ask to **GO DEEPER** on a subtopic -> Elaborate using your research findings\n- If they describe something they want to **CREATE** -> Write ONE perfect prompt (see below)\n- If they ask for a **PROMPT** explicitly -> Write ONE perfect prompt (see below)\n\n**Only write a prompt when the user wants one.** Don't force a prompt on someone who asked \"what could happen next with Iran.\"\n\n### Writing a Prompt\n\nWhen the user wants a prompt, write a **single, highly-tailored prompt** using your research expertise.\n\n### CRITICAL: Match the FORMAT the research recommends\n\n**If research says to use a specific prompt FORMAT, YOU MUST USE THAT FORMAT.**\n\n**ANTI-PATTERN**: Research says \"use JSON prompts with device specs\" but you write plain prose. This defeats the entire purpose of the research.\n\n### Quality Checklist (run before delivering):\n- [ ] **FORMAT MATCHES RESEARCH** - If research said JSON\u002Fstructured\u002Fetc, prompt IS that format\n- [ ] Directly addresses what the user said they want to create\n- [ ] Uses specific patterns\u002Fkeywords discovered in research\n- [ ] Ready to paste with zero edits (or minimal [PLACEHOLDERS] clearly marked)\n- [ ] Appropriate length and style for TARGET_TOOL\n\n### Output Format:\n\n```\nHere's your prompt for {TARGET_TOOL}:\n\n---\n\n[The actual prompt IN THE FORMAT THE RESEARCH RECOMMENDS]\n\n---\n\nThis uses [brief 1-line explanation of what research insight you applied].\n```\n\n---\n\n## IF USER ASKS FOR MORE OPTIONS\n\nOnly if they ask for alternatives or more prompts, provide 2-3 variations. Don't dump a prompt pack unless requested.\n\n---\n\n## AFTER EACH PROMPT: Stay in Expert Mode\n\nAfter delivering a prompt, offer to write more:\n\n> Want another prompt? Just tell me what you're creating next.\n\n---\n\n## CONTEXT MEMORY\n\nFor the rest of this conversation, remember:\n- **TOPIC**: {topic}\n- **TARGET_TOOL**: {tool}\n- **KEY PATTERNS**: {list the top 3-5 patterns you learned}\n- **RESEARCH FINDINGS**: The key facts and insights from the research\n\n**CRITICAL: After research is complete, you are now an EXPERT on this topic.**\n\nWhen the user asks follow-up questions:\n- **DO NOT run new WebSearches** - you already have the research\n- **Answer from what you learned** - cite the Reddit threads, X posts, and web sources\n- **If they ask a question** - answer it from your research findings\n- **If they ask for a prompt** - write one using your expertise\n\nOnly do new research if the user explicitly asks about a DIFFERENT topic.\n\n---\n\n## Output Summary Footer (After Each Prompt)\n\nAfter delivering a prompt, end with:\n\n```\n---\nExpert in: {TOPIC} for {TARGET_TOOL}\nBased on: {n} Reddit threads ({sum} upvotes) + {n} X posts ({sum} likes) + {n} web pages\n\nWant another prompt? Just tell me what you're creating next.\n```\n",{"data":35,"body":44},{"name":4,"description":6,"argument-hint":36,"allowed-tools":37},"nano banana pro prompts, NVIDIA news, best AI video tools",[38,39,40,41,42,43],"Bash","Read","Write","AskUserQuestion","WebSearch","mcp__exa__web_search_exa",{"type":45,"children":46},"root",[47,56,62,69,94,100,123,129,134,212,217,285,293,306,314,344,354,366,371,376,380,386,394,455,460,478,481,487,492,504,509,519,558,568,596,606,634,644,672,677,710,720,769,772,778,786,791,819,827,830,836,844,849,882,892,899,907,912,935,943,952,960,968,974,979,1007,1010,1016,1024,1032,1041,1050,1058,1081,1091,1096,1119,1124,1142,1147,1152,1193,1221,1231,1240,1248,1256,1290,1298,1307,1312,1322,1330,1340,1348,1357,1365,1374,1382,1391,1399,1408,1416,1428,1459,1471,1497,1509,1535,1538,1544,1556,1559,1565,1573,1624,1634,1640,1652,1658,1666,1676,1682,1750,1756,1765,1768,1774,1779,1782,1788,1793,1801,1804,1810,1815,1857,1865,1870,1913,1918,1921,1927,1932,1941],{"type":48,"tag":49,"props":50,"children":52},"element","h1",{"id":51},"last30days-research-any-topic-from-the-last-30-days",[53],{"type":54,"value":55},"text","last30days: Research Any Topic from the Last 30 Days",{"type":48,"tag":57,"props":58,"children":59},"p",{},[60],{"type":54,"value":61},"Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.",{"type":48,"tag":63,"props":64,"children":66},"h2",{"id":65},"when-to-use",[67],{"type":54,"value":68},"When to Use",{"type":48,"tag":70,"props":71,"children":72},"ul",{},[73,79,84,89],{"type":48,"tag":74,"props":75,"children":76},"li",{},[77],{"type":54,"value":78},"User wants to know what people are saying about a topic in the last 30 days",{"type":48,"tag":74,"props":80,"children":81},{},[82],{"type":54,"value":83},"User asks for recent community sentiment, recommendations, or trending discussions",{"type":48,"tag":74,"props":85,"children":86},{},[87],{"type":54,"value":88},"User wants to research a topic before making a decision (tools, products, techniques)",{"type":48,"tag":74,"props":90,"children":91},{},[92],{"type":54,"value":93},"User asks \"what's new with X\" or \"best Y\" or \"what are people saying about Z\"",{"type":48,"tag":63,"props":95,"children":97},{"id":96},"when-not-to-use",[98],{"type":54,"value":99},"When NOT to Use",{"type":48,"tag":70,"props":101,"children":102},{},[103,108,113,118],{"type":48,"tag":74,"props":104,"children":105},{},[106],{"type":54,"value":107},"User wants historical data older than 30 days",{"type":48,"tag":74,"props":109,"children":110},{},[111],{"type":54,"value":112},"User needs official documentation or API references (use docs tools instead)",{"type":48,"tag":74,"props":114,"children":115},{},[116],{"type":54,"value":117},"User wants to search a specific codebase (use code search tools)",{"type":48,"tag":74,"props":119,"children":120},{},[121],{"type":54,"value":122},"User asks a factual question that doesn't need community sentiment",{"type":48,"tag":63,"props":124,"children":126},{"id":125},"critical-parse-user-intent",[127],{"type":54,"value":128},"CRITICAL: Parse User Intent",{"type":48,"tag":57,"props":130,"children":131},{},[132],{"type":54,"value":133},"Before doing anything, parse the user's input for:",{"type":48,"tag":135,"props":136,"children":137},"ol",{},[138,149,159],{"type":48,"tag":74,"props":139,"children":140},{},[141,147],{"type":48,"tag":142,"props":143,"children":144},"strong",{},[145],{"type":54,"value":146},"TOPIC",{"type":54,"value":148},": What they want to learn about (e.g., \"web app mockups\", \"Claude Code skills\", \"image generation\")",{"type":48,"tag":74,"props":150,"children":151},{},[152,157],{"type":48,"tag":142,"props":153,"children":154},{},[155],{"type":54,"value":156},"TARGET TOOL",{"type":54,"value":158}," (if specified): Where they'll use the prompts (e.g., \"Nano Banana Pro\", \"ChatGPT\", \"Midjourney\")",{"type":48,"tag":74,"props":160,"children":161},{},[162,167,169],{"type":48,"tag":142,"props":163,"children":164},{},[165],{"type":54,"value":166},"QUERY TYPE",{"type":54,"value":168},": What kind of research they want:\n",{"type":48,"tag":70,"props":170,"children":171},{},[172,182,192,202],{"type":48,"tag":74,"props":173,"children":174},{},[175,180],{"type":48,"tag":142,"props":176,"children":177},{},[178],{"type":54,"value":179},"PROMPTING",{"type":54,"value":181}," - \"X prompts\", \"prompting for X\", \"X best practices\" -> User wants to learn techniques and get copy-paste prompts",{"type":48,"tag":74,"props":183,"children":184},{},[185,190],{"type":48,"tag":142,"props":186,"children":187},{},[188],{"type":54,"value":189},"RECOMMENDATIONS",{"type":54,"value":191}," - \"best X\", \"top X\", \"what X should I use\", \"recommended X\" -> User wants a LIST of specific things",{"type":48,"tag":74,"props":193,"children":194},{},[195,200],{"type":48,"tag":142,"props":196,"children":197},{},[198],{"type":54,"value":199},"NEWS",{"type":54,"value":201}," - \"what's happening with X\", \"X news\", \"latest on X\" -> User wants current events\u002Fupdates",{"type":48,"tag":74,"props":203,"children":204},{},[205,210],{"type":48,"tag":142,"props":206,"children":207},{},[208],{"type":54,"value":209},"GENERAL",{"type":54,"value":211}," - anything else -> User wants broad understanding of the topic",{"type":48,"tag":57,"props":213,"children":214},{},[215],{"type":54,"value":216},"Common patterns:",{"type":48,"tag":70,"props":218,"children":219},{},[220,232,243,256,275],{"type":48,"tag":74,"props":221,"children":222},{},[223,230],{"type":48,"tag":224,"props":225,"children":227},"code",{"className":226},[],[228],{"type":54,"value":229},"[topic] for [tool]",{"type":54,"value":231}," -> \"web mockups for Nano Banana Pro\" -> TOOL IS SPECIFIED",{"type":48,"tag":74,"props":233,"children":234},{},[235,241],{"type":48,"tag":224,"props":236,"children":238},{"className":237},[],[239],{"type":54,"value":240},"[topic] prompts for [tool]",{"type":54,"value":242}," -> \"UI design prompts for Midjourney\" -> TOOL IS SPECIFIED",{"type":48,"tag":74,"props":244,"children":245},{},[246,248,254],{"type":54,"value":247},"Just ",{"type":48,"tag":224,"props":249,"children":251},{"className":250},[],[252],{"type":54,"value":253},"[topic]",{"type":54,"value":255}," -> \"iOS design mockups\" -> TOOL NOT SPECIFIED, that's OK",{"type":48,"tag":74,"props":257,"children":258},{},[259,261,267,269,273],{"type":54,"value":260},"\"best ",{"type":48,"tag":262,"props":263,"children":264},"span",{},[265],{"type":54,"value":266},"topic",{"type":54,"value":268},"\" or \"top ",{"type":48,"tag":262,"props":270,"children":271},{},[272],{"type":54,"value":266},{"type":54,"value":274},"\" -> QUERY_TYPE = RECOMMENDATIONS",{"type":48,"tag":74,"props":276,"children":277},{},[278,280,284],{"type":54,"value":279},"\"what are the best ",{"type":48,"tag":262,"props":281,"children":282},{},[283],{"type":54,"value":266},{"type":54,"value":274},{"type":48,"tag":57,"props":286,"children":287},{},[288],{"type":48,"tag":142,"props":289,"children":290},{},[291],{"type":54,"value":292},"IMPORTANT: Do NOT ask about target tool before research.",{"type":48,"tag":70,"props":294,"children":295},{},[296,301],{"type":48,"tag":74,"props":297,"children":298},{},[299],{"type":54,"value":300},"If tool is specified in the query, use it",{"type":48,"tag":74,"props":302,"children":303},{},[304],{"type":54,"value":305},"If tool is NOT specified, run research first, then ask AFTER showing results",{"type":48,"tag":57,"props":307,"children":308},{},[309],{"type":48,"tag":142,"props":310,"children":311},{},[312],{"type":54,"value":313},"Store these variables:",{"type":48,"tag":70,"props":315,"children":316},{},[317,326,335],{"type":48,"tag":74,"props":318,"children":319},{},[320],{"type":48,"tag":224,"props":321,"children":323},{"className":322},[],[324],{"type":54,"value":325},"TOPIC = [extracted topic]",{"type":48,"tag":74,"props":327,"children":328},{},[329],{"type":48,"tag":224,"props":330,"children":332},{"className":331},[],[333],{"type":54,"value":334},"TARGET_TOOL = [extracted tool, or \"unknown\" if not specified]",{"type":48,"tag":74,"props":336,"children":337},{},[338],{"type":48,"tag":224,"props":339,"children":341},{"className":340},[],[342],{"type":54,"value":343},"QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]",{"type":48,"tag":57,"props":345,"children":346},{},[347,352],{"type":48,"tag":142,"props":348,"children":349},{},[350],{"type":54,"value":351},"DISPLAY your parsing to the user.",{"type":54,"value":353}," Before running any tools, output:",{"type":48,"tag":355,"props":356,"children":360},"pre",{"className":357,"code":359,"language":54},[358],"language-text","I'll research {TOPIC} across Reddit, X, and the web to find what's been discussed in the last 30 days.\n\nParsed intent:\n- TOPIC = {TOPIC}\n- TARGET_TOOL = {TARGET_TOOL or \"unknown\"}\n- QUERY_TYPE = {QUERY_TYPE}\n\nStarting now.\n",[361],{"type":48,"tag":224,"props":362,"children":364},{"__ignoreMap":363},"",[365],{"type":54,"value":359},{"type":48,"tag":57,"props":367,"children":368},{},[369],{"type":54,"value":370},"If TARGET_TOOL is known, mention it in the intro: \"...to find {QUERY_TYPE}-style content for use in {TARGET_TOOL}.\"",{"type":48,"tag":57,"props":372,"children":373},{},[374],{"type":54,"value":375},"This text MUST appear before you call any tools. It confirms to the user that you understood their request.",{"type":48,"tag":377,"props":378,"children":379},"hr",{},[],{"type":48,"tag":63,"props":381,"children":383},{"id":382},"research-execution",[384],{"type":54,"value":385},"Research Execution",{"type":48,"tag":57,"props":387,"children":388},{},[389],{"type":48,"tag":142,"props":390,"children":391},{},[392],{"type":54,"value":393},"Step 1: Run the research script",{"type":48,"tag":355,"props":395,"children":399},{"className":396,"code":397,"language":398,"meta":363,"style":363},"language-bash shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","python3 \"{baseDir}\u002Fscripts\u002Flast30days.py\" \"$ARGUMENTS\" --emit=compact 2>&1\n","bash",[400],{"type":48,"tag":224,"props":401,"children":402},{"__ignoreMap":363},[403],{"type":48,"tag":262,"props":404,"children":407},{"class":405,"line":406},"line",1,[408,414,420,426,431,435,441,445,450],{"type":48,"tag":262,"props":409,"children":411},{"style":410},"--shiki-light:#E2931D;--shiki-default:#FFCB6B;--shiki-dark:#FFCB6B",[412],{"type":54,"value":413},"python3",{"type":48,"tag":262,"props":415,"children":417},{"style":416},"--shiki-light:#39ADB5;--shiki-default:#89DDFF;--shiki-dark:#89DDFF",[418],{"type":54,"value":419}," \"",{"type":48,"tag":262,"props":421,"children":423},{"style":422},"--shiki-light:#91B859;--shiki-default:#C3E88D;--shiki-dark:#C3E88D",[424],{"type":54,"value":425},"{baseDir}\u002Fscripts\u002Flast30days.py",{"type":48,"tag":262,"props":427,"children":428},{"style":416},[429],{"type":54,"value":430},"\"",{"type":48,"tag":262,"props":432,"children":433},{"style":416},[434],{"type":54,"value":419},{"type":48,"tag":262,"props":436,"children":438},{"style":437},"--shiki-light:#90A4AE;--shiki-default:#EEFFFF;--shiki-dark:#BABED8",[439],{"type":54,"value":440},"$ARGUMENTS",{"type":48,"tag":262,"props":442,"children":443},{"style":416},[444],{"type":54,"value":430},{"type":48,"tag":262,"props":446,"children":447},{"style":422},[448],{"type":54,"value":449}," --emit=compact",{"type":48,"tag":262,"props":451,"children":452},{"style":416},[453],{"type":54,"value":454}," 2>&1\n",{"type":48,"tag":57,"props":456,"children":457},{},[458],{"type":54,"value":459},"The script will automatically:",{"type":48,"tag":70,"props":461,"children":462},{},[463,468,473],{"type":48,"tag":74,"props":464,"children":465},{},[466],{"type":54,"value":467},"Detect available API keys",{"type":48,"tag":74,"props":469,"children":470},{},[471],{"type":54,"value":472},"Run Reddit\u002FX searches if keys exist",{"type":48,"tag":74,"props":474,"children":475},{},[476],{"type":54,"value":477},"Signal if WebSearch is needed",{"type":48,"tag":377,"props":479,"children":480},{},[],{"type":48,"tag":63,"props":482,"children":484},{"id":483},"step-2-do-websearch-while-script-runs",[485],{"type":54,"value":486},"STEP 2: DO WEBSEARCH WHILE SCRIPT RUNS",{"type":48,"tag":57,"props":488,"children":489},{},[490],{"type":54,"value":491},"The script auto-detects sources (API keys, etc). While waiting for it, do WebSearch.",{"type":48,"tag":57,"props":493,"children":494},{},[495,497,502],{"type":54,"value":496},"For ",{"type":48,"tag":142,"props":498,"children":499},{},[500],{"type":54,"value":501},"ALL modes",{"type":54,"value":503},", do WebSearch to supplement (or provide all data in web-only mode).",{"type":48,"tag":57,"props":505,"children":506},{},[507],{"type":54,"value":508},"Choose search queries based on QUERY_TYPE:",{"type":48,"tag":57,"props":510,"children":511},{},[512,517],{"type":48,"tag":142,"props":513,"children":514},{},[515],{"type":54,"value":516},"If RECOMMENDATIONS",{"type":54,"value":518}," (\"best X\", \"top X\", \"what X should I use\"):",{"type":48,"tag":70,"props":520,"children":521},{},[522,533,543,553],{"type":48,"tag":74,"props":523,"children":524},{},[525,527],{"type":54,"value":526},"Search for: ",{"type":48,"tag":224,"props":528,"children":530},{"className":529},[],[531],{"type":54,"value":532},"best {TOPIC} recommendations",{"type":48,"tag":74,"props":534,"children":535},{},[536,537],{"type":54,"value":526},{"type":48,"tag":224,"props":538,"children":540},{"className":539},[],[541],{"type":54,"value":542},"{TOPIC} list examples",{"type":48,"tag":74,"props":544,"children":545},{},[546,547],{"type":54,"value":526},{"type":48,"tag":224,"props":548,"children":550},{"className":549},[],[551],{"type":54,"value":552},"most popular {TOPIC}",{"type":48,"tag":74,"props":554,"children":555},{},[556],{"type":54,"value":557},"Goal: Find SPECIFIC NAMES of things, not generic advice",{"type":48,"tag":57,"props":559,"children":560},{},[561,566],{"type":48,"tag":142,"props":562,"children":563},{},[564],{"type":54,"value":565},"If NEWS",{"type":54,"value":567}," (\"what's happening with X\", \"X news\"):",{"type":48,"tag":70,"props":569,"children":570},{},[571,581,591],{"type":48,"tag":74,"props":572,"children":573},{},[574,575],{"type":54,"value":526},{"type":48,"tag":224,"props":576,"children":578},{"className":577},[],[579],{"type":54,"value":580},"{TOPIC} news 2026",{"type":48,"tag":74,"props":582,"children":583},{},[584,585],{"type":54,"value":526},{"type":48,"tag":224,"props":586,"children":588},{"className":587},[],[589],{"type":54,"value":590},"{TOPIC} announcement update",{"type":48,"tag":74,"props":592,"children":593},{},[594],{"type":54,"value":595},"Goal: Find current events and recent developments",{"type":48,"tag":57,"props":597,"children":598},{},[599,604],{"type":48,"tag":142,"props":600,"children":601},{},[602],{"type":54,"value":603},"If PROMPTING",{"type":54,"value":605}," (\"X prompts\", \"prompting for X\"):",{"type":48,"tag":70,"props":607,"children":608},{},[609,619,629],{"type":48,"tag":74,"props":610,"children":611},{},[612,613],{"type":54,"value":526},{"type":48,"tag":224,"props":614,"children":616},{"className":615},[],[617],{"type":54,"value":618},"{TOPIC} prompts examples 2026",{"type":48,"tag":74,"props":620,"children":621},{},[622,623],{"type":54,"value":526},{"type":48,"tag":224,"props":624,"children":626},{"className":625},[],[627],{"type":54,"value":628},"{TOPIC} techniques tips",{"type":48,"tag":74,"props":630,"children":631},{},[632],{"type":54,"value":633},"Goal: Find prompting techniques and examples to create copy-paste prompts",{"type":48,"tag":57,"props":635,"children":636},{},[637,642],{"type":48,"tag":142,"props":638,"children":639},{},[640],{"type":54,"value":641},"If GENERAL",{"type":54,"value":643}," (default):",{"type":48,"tag":70,"props":645,"children":646},{},[647,657,667],{"type":48,"tag":74,"props":648,"children":649},{},[650,651],{"type":54,"value":526},{"type":48,"tag":224,"props":652,"children":654},{"className":653},[],[655],{"type":54,"value":656},"{TOPIC} 2026",{"type":48,"tag":74,"props":658,"children":659},{},[660,661],{"type":54,"value":526},{"type":48,"tag":224,"props":662,"children":664},{"className":663},[],[665],{"type":54,"value":666},"{TOPIC} discussion",{"type":48,"tag":74,"props":668,"children":669},{},[670],{"type":54,"value":671},"Goal: Find what people are actually saying",{"type":48,"tag":57,"props":673,"children":674},{},[675],{"type":54,"value":676},"For ALL query types:",{"type":48,"tag":70,"props":678,"children":679},{},[680,690,695,700],{"type":48,"tag":74,"props":681,"children":682},{},[683,688],{"type":48,"tag":142,"props":684,"children":685},{},[686],{"type":54,"value":687},"USE THE USER'S EXACT TERMINOLOGY",{"type":54,"value":689}," - don't substitute or add tech names based on your knowledge",{"type":48,"tag":74,"props":691,"children":692},{},[693],{"type":54,"value":694},"EXCLUDE reddit.com, x.com, twitter.com (covered by script)",{"type":48,"tag":74,"props":696,"children":697},{},[698],{"type":54,"value":699},"INCLUDE: blogs, tutorials, docs, news, GitHub repos",{"type":48,"tag":74,"props":701,"children":702},{},[703,708],{"type":48,"tag":142,"props":704,"children":705},{},[706],{"type":54,"value":707},"DO NOT output \"Sources:\" list",{"type":54,"value":709}," - this is noise, we'll show stats at the end",{"type":48,"tag":57,"props":711,"children":712},{},[713,718],{"type":48,"tag":142,"props":714,"children":715},{},[716],{"type":54,"value":717},"Options",{"type":54,"value":719}," (passed through from user's command):",{"type":48,"tag":70,"props":721,"children":722},{},[723,742,753,758],{"type":48,"tag":74,"props":724,"children":725},{},[726,732,734,740],{"type":48,"tag":224,"props":727,"children":729},{"className":728},[],[730],{"type":54,"value":731},"--days=N",{"type":54,"value":733}," -> Look back N days instead of 30 (e.g., ",{"type":48,"tag":224,"props":735,"children":737},{"className":736},[],[738],{"type":54,"value":739},"--days=7",{"type":54,"value":741}," for weekly roundup)",{"type":48,"tag":74,"props":743,"children":744},{},[745,751],{"type":48,"tag":224,"props":746,"children":748},{"className":747},[],[749],{"type":54,"value":750},"--quick",{"type":54,"value":752}," -> Faster, fewer sources (8-12 each)",{"type":48,"tag":74,"props":754,"children":755},{},[756],{"type":54,"value":757},"(default) -> Balanced (20-30 each)",{"type":48,"tag":74,"props":759,"children":760},{},[761,767],{"type":48,"tag":224,"props":762,"children":764},{"className":763},[],[765],{"type":54,"value":766},"--deep",{"type":54,"value":768}," -> Comprehensive (50-70 Reddit, 40-60 X)",{"type":48,"tag":377,"props":770,"children":771},{},[],{"type":48,"tag":63,"props":773,"children":775},{"id":774},"judge-agent-synthesize-all-sources",[776],{"type":54,"value":777},"Judge Agent: Synthesize All Sources",{"type":48,"tag":57,"props":779,"children":780},{},[781],{"type":48,"tag":142,"props":782,"children":783},{},[784],{"type":54,"value":785},"After all searches complete, internally synthesize (don't display stats yet):",{"type":48,"tag":57,"props":787,"children":788},{},[789],{"type":54,"value":790},"The Judge Agent must:",{"type":48,"tag":135,"props":792,"children":793},{},[794,799,804,809,814],{"type":48,"tag":74,"props":795,"children":796},{},[797],{"type":54,"value":798},"Weight Reddit\u002FX sources HIGHER (they have engagement signals: upvotes, likes)",{"type":48,"tag":74,"props":800,"children":801},{},[802],{"type":54,"value":803},"Weight WebSearch sources LOWER (no engagement data)",{"type":48,"tag":74,"props":805,"children":806},{},[807],{"type":54,"value":808},"Identify patterns that appear across ALL three sources (strongest signals)",{"type":48,"tag":74,"props":810,"children":811},{},[812],{"type":54,"value":813},"Note any contradictions between sources",{"type":48,"tag":74,"props":815,"children":816},{},[817],{"type":54,"value":818},"Extract the top 3-5 actionable insights",{"type":48,"tag":57,"props":820,"children":821},{},[822],{"type":48,"tag":142,"props":823,"children":824},{},[825],{"type":54,"value":826},"Do NOT display stats here - they come at the end, right before the invitation.",{"type":48,"tag":377,"props":828,"children":829},{},[],{"type":48,"tag":63,"props":831,"children":833},{"id":832},"first-internalize-the-research",[834],{"type":54,"value":835},"FIRST: Internalize the Research",{"type":48,"tag":57,"props":837,"children":838},{},[839],{"type":48,"tag":142,"props":840,"children":841},{},[842],{"type":54,"value":843},"CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.",{"type":48,"tag":57,"props":845,"children":846},{},[847],{"type":54,"value":848},"Read the research output carefully. Pay attention to:",{"type":48,"tag":70,"props":850,"children":851},{},[852,862,872],{"type":48,"tag":74,"props":853,"children":854},{},[855,860],{"type":48,"tag":142,"props":856,"children":857},{},[858],{"type":54,"value":859},"Exact product\u002Ftool names",{"type":54,"value":861}," mentioned (e.g., if research mentions \"ClawdBot\" or \"@clawdbot\", that's a DIFFERENT product than \"Claude Code\" - don't conflate them)",{"type":48,"tag":74,"props":863,"children":864},{},[865,870],{"type":48,"tag":142,"props":866,"children":867},{},[868],{"type":54,"value":869},"Specific quotes and insights",{"type":54,"value":871}," from the sources - use THESE, not generic knowledge",{"type":48,"tag":74,"props":873,"children":874},{},[875,880],{"type":48,"tag":142,"props":876,"children":877},{},[878],{"type":54,"value":879},"What the sources actually say",{"type":54,"value":881},", not what you assume the topic is about",{"type":48,"tag":57,"props":883,"children":884},{},[885,890],{"type":48,"tag":142,"props":886,"children":887},{},[888],{"type":54,"value":889},"ANTI-PATTERN TO AVOID",{"type":54,"value":891},": If user asks about \"clawdbot skills\" and research returns ClawdBot content (self-hosted AI agent), do NOT synthesize this as \"Claude Code skills\" just because both involve \"skills\". Read what the research actually says.",{"type":48,"tag":893,"props":894,"children":896},"h3",{"id":895},"if-query_type-recommendations",[897],{"type":54,"value":898},"If QUERY_TYPE = RECOMMENDATIONS",{"type":48,"tag":57,"props":900,"children":901},{},[902],{"type":48,"tag":142,"props":903,"children":904},{},[905],{"type":54,"value":906},"CRITICAL: Extract SPECIFIC NAMES, not generic patterns.",{"type":48,"tag":57,"props":908,"children":909},{},[910],{"type":54,"value":911},"When user asks \"best X\" or \"top X\", they want a LIST of specific things:",{"type":48,"tag":70,"props":913,"children":914},{},[915,920,925,930],{"type":48,"tag":74,"props":916,"children":917},{},[918],{"type":54,"value":919},"Scan research for specific product names, tool names, project names, skill names, etc.",{"type":48,"tag":74,"props":921,"children":922},{},[923],{"type":54,"value":924},"Count how many times each is mentioned",{"type":48,"tag":74,"props":926,"children":927},{},[928],{"type":54,"value":929},"Note which sources recommend each (Reddit thread, X post, blog)",{"type":48,"tag":74,"props":931,"children":932},{},[933],{"type":54,"value":934},"List them by popularity\u002Fmention count",{"type":48,"tag":57,"props":936,"children":937},{},[938],{"type":48,"tag":142,"props":939,"children":940},{},[941],{"type":54,"value":942},"BAD synthesis for \"best Claude Code skills\":",{"type":48,"tag":944,"props":945,"children":946},"blockquote",{},[947],{"type":48,"tag":57,"props":948,"children":949},{},[950],{"type":54,"value":951},"\"Skills are powerful. Keep them under 500 lines. Use progressive disclosure.\"",{"type":48,"tag":57,"props":953,"children":954},{},[955],{"type":48,"tag":142,"props":956,"children":957},{},[958],{"type":54,"value":959},"GOOD synthesis for \"best Claude Code skills\":",{"type":48,"tag":944,"props":961,"children":962},{},[963],{"type":48,"tag":57,"props":964,"children":965},{},[966],{"type":54,"value":967},"\"Most mentioned skills: \u002Fcommit (5 mentions), remotion skill (4x), git-worktree (3x), \u002Fpr (3x). The Remotion announcement got 16K likes on X.\"",{"type":48,"tag":893,"props":969,"children":971},{"id":970},"for-all-query_types",[972],{"type":54,"value":973},"For all QUERY_TYPEs",{"type":48,"tag":57,"props":975,"children":976},{},[977],{"type":54,"value":978},"Identify from the ACTUAL RESEARCH OUTPUT:",{"type":48,"tag":70,"props":980,"children":981},{},[982,992,997,1002],{"type":48,"tag":74,"props":983,"children":984},{},[985,990],{"type":48,"tag":142,"props":986,"children":987},{},[988],{"type":54,"value":989},"PROMPT FORMAT",{"type":54,"value":991}," - Does research recommend JSON, structured params, natural language, keywords?",{"type":48,"tag":74,"props":993,"children":994},{},[995],{"type":54,"value":996},"The top 3-5 patterns\u002Ftechniques that appeared across multiple sources",{"type":48,"tag":74,"props":998,"children":999},{},[1000],{"type":54,"value":1001},"Specific keywords, structures, or approaches mentioned BY THE SOURCES",{"type":48,"tag":74,"props":1003,"children":1004},{},[1005],{"type":54,"value":1006},"Common pitfalls mentioned BY THE SOURCES",{"type":48,"tag":377,"props":1008,"children":1009},{},[],{"type":48,"tag":63,"props":1011,"children":1013},{"id":1012},"then-show-summary-invite-vision",[1014],{"type":54,"value":1015},"THEN: Show Summary + Invite Vision",{"type":48,"tag":57,"props":1017,"children":1018},{},[1019],{"type":48,"tag":142,"props":1020,"children":1021},{},[1022],{"type":54,"value":1023},"Display in this EXACT sequence:",{"type":48,"tag":57,"props":1025,"children":1026},{},[1027],{"type":48,"tag":142,"props":1028,"children":1029},{},[1030],{"type":54,"value":1031},"FIRST - What I learned (based on QUERY_TYPE):",{"type":48,"tag":57,"props":1033,"children":1034},{},[1035,1039],{"type":48,"tag":142,"props":1036,"children":1037},{},[1038],{"type":54,"value":516},{"type":54,"value":1040}," - Show specific things mentioned with sources:",{"type":48,"tag":355,"props":1042,"children":1045},{"className":1043,"code":1044,"language":54},[358],"Most mentioned:\n\n[Tool Name] - {n}x mentions\nUse Case: [what it does]\nSources: @handle1, @handle2, r\u002Fsub, blog.com\n\n[Tool Name] - {n}x mentions\nUse Case: [what it does]\nSources: @handle3, r\u002Fsub2, Complex\n\nNotable mentions: [other specific things with 1-2 mentions]\n",[1046],{"type":48,"tag":224,"props":1047,"children":1048},{"__ignoreMap":363},[1049],{"type":54,"value":1044},{"type":48,"tag":57,"props":1051,"children":1052},{},[1053],{"type":48,"tag":142,"props":1054,"children":1055},{},[1056],{"type":54,"value":1057},"CRITICAL for RECOMMENDATIONS:",{"type":48,"tag":70,"props":1059,"children":1060},{},[1061,1066,1071,1076],{"type":48,"tag":74,"props":1062,"children":1063},{},[1064],{"type":54,"value":1065},"Each item MUST have a \"Sources:\" line with actual @handles from X posts (e.g., @LONGLIVE47, @ByDobson)",{"type":48,"tag":74,"props":1067,"children":1068},{},[1069],{"type":54,"value":1070},"Include subreddit names (r\u002Fhiphopheads) and web sources (Complex, Variety)",{"type":48,"tag":74,"props":1072,"children":1073},{},[1074],{"type":54,"value":1075},"Parse @handles from research output and include the highest-engagement ones",{"type":48,"tag":74,"props":1077,"children":1078},{},[1079],{"type":54,"value":1080},"Format naturally - tables work well for wide terminals, stacked cards for narrow",{"type":48,"tag":57,"props":1082,"children":1083},{},[1084,1089],{"type":48,"tag":142,"props":1085,"children":1086},{},[1087],{"type":54,"value":1088},"If PROMPTING\u002FNEWS\u002FGENERAL",{"type":54,"value":1090}," - Show synthesis and patterns:",{"type":48,"tag":57,"props":1092,"children":1093},{},[1094],{"type":54,"value":1095},"CITATION RULE: Cite sources sparingly to prove research is real.",{"type":48,"tag":70,"props":1097,"children":1098},{},[1099,1104,1109,1114],{"type":48,"tag":74,"props":1100,"children":1101},{},[1102],{"type":54,"value":1103},"In the \"What I learned\" intro: cite 1-2 top sources total, not every sentence",{"type":48,"tag":74,"props":1105,"children":1106},{},[1107],{"type":54,"value":1108},"In KEY PATTERNS: cite 1 source per pattern, short format: \"per @handle\" or \"per r\u002Fsub\"",{"type":48,"tag":74,"props":1110,"children":1111},{},[1112],{"type":54,"value":1113},"Do NOT include engagement metrics in citations (likes, upvotes) - save those for stats box",{"type":48,"tag":74,"props":1115,"children":1116},{},[1117],{"type":54,"value":1118},"Do NOT chain multiple citations: \"per @x, @y, @z\" is too much. Pick the strongest one.",{"type":48,"tag":57,"props":1120,"children":1121},{},[1122],{"type":54,"value":1123},"CITATION PRIORITY (most to least preferred):",{"type":48,"tag":135,"props":1125,"children":1126},{},[1127,1132,1137],{"type":48,"tag":74,"props":1128,"children":1129},{},[1130],{"type":54,"value":1131},"@handles from X -- \"per @handle\" (these prove the tool's unique value)",{"type":48,"tag":74,"props":1133,"children":1134},{},[1135],{"type":54,"value":1136},"r\u002Fsubreddits from Reddit -- \"per r\u002Fsubreddit\"",{"type":48,"tag":74,"props":1138,"children":1139},{},[1140],{"type":54,"value":1141},"Web sources -- ONLY when Reddit\u002FX don't cover that specific fact",{"type":48,"tag":57,"props":1143,"children":1144},{},[1145],{"type":54,"value":1146},"The tool's value is surfacing what PEOPLE are saying, not what journalists wrote.\nWhen both a web article and an X post cover the same fact, cite the X post.",{"type":48,"tag":57,"props":1148,"children":1149},{},[1150],{"type":54,"value":1151},"URL FORMATTING: NEVER paste raw URLs in the output.",{"type":48,"tag":70,"props":1153,"children":1154},{},[1155,1174,1184],{"type":48,"tag":74,"props":1156,"children":1157},{},[1158,1163,1165,1173],{"type":48,"tag":142,"props":1159,"children":1160},{},[1161],{"type":54,"value":1162},"BAD:",{"type":54,"value":1164}," \"per ",{"type":48,"tag":1166,"props":1167,"children":1171},"a",{"href":1168,"rel":1169},"https:\u002F\u002Fwww.rollingstone.com\u002Fmusic\u002Fmusic-news\u002Fkanye-west-bully-1235506094\u002F",[1170],"nofollow",[1172],{"type":54,"value":1168},{"type":54,"value":430},{"type":48,"tag":74,"props":1175,"children":1176},{},[1177,1182],{"type":48,"tag":142,"props":1178,"children":1179},{},[1180],{"type":54,"value":1181},"GOOD:",{"type":54,"value":1183}," \"per Rolling Stone\"",{"type":48,"tag":74,"props":1185,"children":1186},{},[1187,1191],{"type":48,"tag":142,"props":1188,"children":1189},{},[1190],{"type":54,"value":1181},{"type":54,"value":1192}," \"per Complex\"\nUse the publication name, not the URL. The user doesn't need links -- they need clean, readable text.",{"type":48,"tag":57,"props":1194,"children":1195},{},[1196,1200,1202,1206,1208,1212,1214,1219],{"type":48,"tag":142,"props":1197,"children":1198},{},[1199],{"type":54,"value":1162},{"type":54,"value":1201}," \"His album is set for March 20 (per Rolling Stone; Billboard; Complex).\"\n",{"type":48,"tag":142,"props":1203,"children":1204},{},[1205],{"type":54,"value":1181},{"type":54,"value":1207}," \"His album BULLY drops March 20 -- fans on X are split on the tracklist, per @honest30bgfan_\"\n",{"type":48,"tag":142,"props":1209,"children":1210},{},[1211],{"type":54,"value":1181},{"type":54,"value":1213}," \"Ye's apology got massive traction on r\u002Fhiphopheads\"\n",{"type":48,"tag":142,"props":1215,"children":1216},{},[1217],{"type":54,"value":1218},"OK",{"type":54,"value":1220}," (web, only when Reddit\u002FX don't have it): \"The Hellwatt Festival runs July 4-18 at RCF Arena, per Billboard\"",{"type":48,"tag":57,"props":1222,"children":1223},{},[1224,1229],{"type":48,"tag":142,"props":1225,"children":1226},{},[1227],{"type":54,"value":1228},"Lead with people, not publications.",{"type":54,"value":1230}," Start each topic with what Reddit\u002FX\nusers are saying\u002Ffeeling, then add web context only if needed. The user came\nhere for the conversation, not the press release.",{"type":48,"tag":355,"props":1232,"children":1235},{"className":1233,"code":1234,"language":54},[358],"What I learned:\n\n**{Topic 1}** -- [1-2 sentences about what people are saying, per @handle or r\u002Fsub]\n\n**{Topic 2}** -- [1-2 sentences, per @handle or r\u002Fsub]\n\n**{Topic 3}** -- [1-2 sentences, per @handle or r\u002Fsub]\n\nKEY PATTERNS from the research:\n1. [Pattern] -- per @handle\n2. [Pattern] -- per r\u002Fsub\n3. [Pattern] -- per @handle\n",[1236],{"type":48,"tag":224,"props":1237,"children":1238},{"__ignoreMap":363},[1239],{"type":54,"value":1234},{"type":48,"tag":57,"props":1241,"children":1242},{},[1243],{"type":48,"tag":142,"props":1244,"children":1245},{},[1246],{"type":54,"value":1247},"THEN - Stats (right before invitation):",{"type":48,"tag":57,"props":1249,"children":1250},{},[1251],{"type":48,"tag":142,"props":1252,"children":1253},{},[1254],{"type":54,"value":1255},"CRITICAL: Calculate actual totals from the research output.",{"type":48,"tag":70,"props":1257,"children":1258},{},[1259,1264,1285],{"type":48,"tag":74,"props":1260,"children":1261},{},[1262],{"type":54,"value":1263},"Count posts\u002Fthreads from each section",{"type":48,"tag":74,"props":1265,"children":1266},{},[1267,1269,1275,1277,1283],{"type":54,"value":1268},"Sum engagement: parse ",{"type":48,"tag":224,"props":1270,"children":1272},{"className":1271},[],[1273],{"type":54,"value":1274},"[Xlikes, Yrt]",{"type":54,"value":1276}," from each X post, ",{"type":48,"tag":224,"props":1278,"children":1280},{"className":1279},[],[1281],{"type":54,"value":1282},"[Xpts, Ycmt]",{"type":54,"value":1284}," from Reddit",{"type":48,"tag":74,"props":1286,"children":1287},{},[1288],{"type":54,"value":1289},"Identify top voices: highest-engagement @handles from X, most active subreddits",{"type":48,"tag":57,"props":1291,"children":1292},{},[1293],{"type":48,"tag":142,"props":1294,"children":1295},{},[1296],{"type":54,"value":1297},"Copy this EXACTLY, replacing only the {placeholders}:",{"type":48,"tag":355,"props":1299,"children":1302},{"className":1300,"code":1301,"language":54},[358],"---\nAll agents reported back!\n|- Reddit: {N} threads | {N} upvotes | {N} comments\n|- X: {N} posts | {N} likes | {N} reposts (via xAI)\n|- Web: {N} pages (supplementary)\n|- Top voices: @{handle1} ({N} likes), @{handle2} | r\u002F{sub1}, r\u002F{sub2}\n---\n",[1303],{"type":48,"tag":224,"props":1304,"children":1305},{"__ignoreMap":363},[1306],{"type":54,"value":1301},{"type":48,"tag":57,"props":1308,"children":1309},{},[1310],{"type":54,"value":1311},"If Reddit returned 0 threads, write: \"|- Reddit: 0 threads (no results this cycle)\"",{"type":48,"tag":57,"props":1313,"children":1314},{},[1315,1320],{"type":48,"tag":142,"props":1316,"children":1317},{},[1318],{"type":54,"value":1319},"SELF-CHECK before displaying",{"type":54,"value":1321},": Re-read your \"What I learned\" section. Does it match what the research ACTUALLY says? If you catch yourself projecting your own knowledge instead of the research, rewrite it.",{"type":48,"tag":57,"props":1323,"children":1324},{},[1325],{"type":48,"tag":142,"props":1326,"children":1327},{},[1328],{"type":54,"value":1329},"LAST - Invitation (adapt to QUERY_TYPE):",{"type":48,"tag":57,"props":1331,"children":1332},{},[1333,1338],{"type":48,"tag":142,"props":1334,"children":1335},{},[1336],{"type":54,"value":1337},"CRITICAL: Every invitation MUST include 2-3 specific example suggestions based on what you ACTUALLY learned from the research.",{"type":54,"value":1339}," Don't be generic -- show the user you absorbed the content by referencing real things from the results.",{"type":48,"tag":57,"props":1341,"children":1342},{},[1343],{"type":48,"tag":142,"props":1344,"children":1345},{},[1346],{"type":54,"value":1347},"If QUERY_TYPE = PROMPTING:",{"type":48,"tag":355,"props":1349,"children":1352},{"className":1350,"code":1351,"language":54},[358],"---\nI'm now an expert on {TOPIC} for {TARGET_TOOL}. What do you want to make? For example:\n- [specific idea based on popular technique from research]\n- [specific idea based on trending style\u002Fapproach from research]\n- [specific idea riffing on what people are actually creating]\n\nJust describe your vision and I'll write a prompt you can paste straight into {TARGET_TOOL}.\n",[1353],{"type":48,"tag":224,"props":1354,"children":1355},{"__ignoreMap":363},[1356],{"type":54,"value":1351},{"type":48,"tag":57,"props":1358,"children":1359},{},[1360],{"type":48,"tag":142,"props":1361,"children":1362},{},[1363],{"type":54,"value":1364},"If QUERY_TYPE = RECOMMENDATIONS:",{"type":48,"tag":355,"props":1366,"children":1369},{"className":1367,"code":1368,"language":54},[358],"---\nI'm now an expert on {TOPIC}. Want me to go deeper? For example:\n- [Compare specific item A vs item B from the results]\n- [Explain why item C is trending right now]\n- [Help you get started with item D]\n",[1370],{"type":48,"tag":224,"props":1371,"children":1372},{"__ignoreMap":363},[1373],{"type":54,"value":1368},{"type":48,"tag":57,"props":1375,"children":1376},{},[1377],{"type":48,"tag":142,"props":1378,"children":1379},{},[1380],{"type":54,"value":1381},"If QUERY_TYPE = NEWS:",{"type":48,"tag":355,"props":1383,"children":1386},{"className":1384,"code":1385,"language":54},[358],"---\nI'm now an expert on {TOPIC}. Some things you could ask:\n- [Specific follow-up question about the biggest story]\n- [Question about implications of a key development]\n- [Question about what might happen next based on current trajectory]\n",[1387],{"type":48,"tag":224,"props":1388,"children":1389},{"__ignoreMap":363},[1390],{"type":54,"value":1385},{"type":48,"tag":57,"props":1392,"children":1393},{},[1394],{"type":48,"tag":142,"props":1395,"children":1396},{},[1397],{"type":54,"value":1398},"If QUERY_TYPE = GENERAL:",{"type":48,"tag":355,"props":1400,"children":1403},{"className":1401,"code":1402,"language":54},[358],"---\nI'm now an expert on {TOPIC}. Some things I can help with:\n- [Specific question based on the most discussed aspect]\n- [Specific creative\u002Fpractical application of what you learned]\n- [Deeper dive into a pattern or debate from the research]\n",[1404],{"type":48,"tag":224,"props":1405,"children":1406},{"__ignoreMap":363},[1407],{"type":54,"value":1402},{"type":48,"tag":57,"props":1409,"children":1410},{},[1411],{"type":48,"tag":142,"props":1412,"children":1413},{},[1414],{"type":54,"value":1415},"Example invitations (to show the quality bar):",{"type":48,"tag":57,"props":1417,"children":1418},{},[1419,1420,1426],{"type":54,"value":496},{"type":48,"tag":224,"props":1421,"children":1423},{"className":1422},[],[1424],{"type":54,"value":1425},"\u002Flast30days nano banana pro prompts for Gemini",{"type":54,"value":1427},":",{"type":48,"tag":944,"props":1429,"children":1430},{},[1431,1436,1454],{"type":48,"tag":57,"props":1432,"children":1433},{},[1434],{"type":54,"value":1435},"I'm now an expert on Nano Banana Pro for Gemini. What do you want to make? For example:",{"type":48,"tag":70,"props":1437,"children":1438},{},[1439,1444,1449],{"type":48,"tag":74,"props":1440,"children":1441},{},[1442],{"type":54,"value":1443},"Photorealistic product shots with natural lighting (the most requested style right now)",{"type":48,"tag":74,"props":1445,"children":1446},{},[1447],{"type":54,"value":1448},"Logo designs with embedded text (Gemini's new strength per the research)",{"type":48,"tag":74,"props":1450,"children":1451},{},[1452],{"type":54,"value":1453},"Multi-reference style transfer from a mood board",{"type":48,"tag":57,"props":1455,"children":1456},{},[1457],{"type":54,"value":1458},"Just describe your vision and I'll write a prompt you can paste straight into Gemini.",{"type":48,"tag":57,"props":1460,"children":1461},{},[1462,1463,1469],{"type":54,"value":496},{"type":48,"tag":224,"props":1464,"children":1466},{"className":1465},[],[1467],{"type":54,"value":1468},"\u002Flast30days kanye west",{"type":54,"value":1470}," (GENERAL):",{"type":48,"tag":944,"props":1472,"children":1473},{},[1474,1479],{"type":48,"tag":57,"props":1475,"children":1476},{},[1477],{"type":54,"value":1478},"I'm now an expert on Kanye West. Some things I can help with:",{"type":48,"tag":70,"props":1480,"children":1481},{},[1482,1487,1492],{"type":48,"tag":74,"props":1483,"children":1484},{},[1485],{"type":54,"value":1486},"What's the real story behind the apology letter -- genuine or PR move?",{"type":48,"tag":74,"props":1488,"children":1489},{},[1490],{"type":54,"value":1491},"Break down the BULLY tracklist reactions and what fans are expecting",{"type":48,"tag":74,"props":1493,"children":1494},{},[1495],{"type":54,"value":1496},"Compare how Reddit vs X are reacting to the Bianca narrative",{"type":48,"tag":57,"props":1498,"children":1499},{},[1500,1501,1507],{"type":54,"value":496},{"type":48,"tag":224,"props":1502,"children":1504},{"className":1503},[],[1505],{"type":54,"value":1506},"\u002Flast30days war in Iran",{"type":54,"value":1508}," (NEWS):",{"type":48,"tag":944,"props":1510,"children":1511},{},[1512,1517],{"type":48,"tag":57,"props":1513,"children":1514},{},[1515],{"type":54,"value":1516},"I'm now an expert on the Iran situation. Some things you could ask:",{"type":48,"tag":70,"props":1518,"children":1519},{},[1520,1525,1530],{"type":48,"tag":74,"props":1521,"children":1522},{},[1523],{"type":54,"value":1524},"What are the realistic escalation scenarios from here?",{"type":48,"tag":74,"props":1526,"children":1527},{},[1528],{"type":54,"value":1529},"How is this playing differently in US vs international media?",{"type":48,"tag":74,"props":1531,"children":1532},{},[1533],{"type":54,"value":1534},"What's the economic impact on oil markets so far?",{"type":48,"tag":377,"props":1536,"children":1537},{},[],{"type":48,"tag":63,"props":1539,"children":1541},{"id":1540},"wait-for-users-response",[1542],{"type":54,"value":1543},"WAIT FOR USER'S RESPONSE",{"type":48,"tag":57,"props":1545,"children":1546},{},[1547,1549,1554],{"type":54,"value":1548},"After showing the stats summary with your invitation, ",{"type":48,"tag":142,"props":1550,"children":1551},{},[1552],{"type":54,"value":1553},"STOP and wait",{"type":54,"value":1555}," for the user to respond.",{"type":48,"tag":377,"props":1557,"children":1558},{},[],{"type":48,"tag":63,"props":1560,"children":1562},{"id":1561},"when-user-responds",[1563],{"type":54,"value":1564},"WHEN USER RESPONDS",{"type":48,"tag":57,"props":1566,"children":1567},{},[1568],{"type":48,"tag":142,"props":1569,"children":1570},{},[1571],{"type":54,"value":1572},"Read their response and match the intent:",{"type":48,"tag":70,"props":1574,"children":1575},{},[1576,1588,1600,1612],{"type":48,"tag":74,"props":1577,"children":1578},{},[1579,1581,1586],{"type":54,"value":1580},"If they ask a ",{"type":48,"tag":142,"props":1582,"children":1583},{},[1584],{"type":54,"value":1585},"QUESTION",{"type":54,"value":1587}," about the topic -> Answer from your research (no new searches, no prompt)",{"type":48,"tag":74,"props":1589,"children":1590},{},[1591,1593,1598],{"type":54,"value":1592},"If they ask to ",{"type":48,"tag":142,"props":1594,"children":1595},{},[1596],{"type":54,"value":1597},"GO DEEPER",{"type":54,"value":1599}," on a subtopic -> Elaborate using your research findings",{"type":48,"tag":74,"props":1601,"children":1602},{},[1603,1605,1610],{"type":54,"value":1604},"If they describe something they want to ",{"type":48,"tag":142,"props":1606,"children":1607},{},[1608],{"type":54,"value":1609},"CREATE",{"type":54,"value":1611}," -> Write ONE perfect prompt (see below)",{"type":48,"tag":74,"props":1613,"children":1614},{},[1615,1617,1622],{"type":54,"value":1616},"If they ask for a ",{"type":48,"tag":142,"props":1618,"children":1619},{},[1620],{"type":54,"value":1621},"PROMPT",{"type":54,"value":1623}," explicitly -> Write ONE perfect prompt (see below)",{"type":48,"tag":57,"props":1625,"children":1626},{},[1627,1632],{"type":48,"tag":142,"props":1628,"children":1629},{},[1630],{"type":54,"value":1631},"Only write a prompt when the user wants one.",{"type":54,"value":1633}," Don't force a prompt on someone who asked \"what could happen next with Iran.\"",{"type":48,"tag":893,"props":1635,"children":1637},{"id":1636},"writing-a-prompt",[1638],{"type":54,"value":1639},"Writing a Prompt",{"type":48,"tag":57,"props":1641,"children":1642},{},[1643,1645,1650],{"type":54,"value":1644},"When the user wants a prompt, write a ",{"type":48,"tag":142,"props":1646,"children":1647},{},[1648],{"type":54,"value":1649},"single, highly-tailored prompt",{"type":54,"value":1651}," using your research expertise.",{"type":48,"tag":893,"props":1653,"children":1655},{"id":1654},"critical-match-the-format-the-research-recommends",[1656],{"type":54,"value":1657},"CRITICAL: Match the FORMAT the research recommends",{"type":48,"tag":57,"props":1659,"children":1660},{},[1661],{"type":48,"tag":142,"props":1662,"children":1663},{},[1664],{"type":54,"value":1665},"If research says to use a specific prompt FORMAT, YOU MUST USE THAT FORMAT.",{"type":48,"tag":57,"props":1667,"children":1668},{},[1669,1674],{"type":48,"tag":142,"props":1670,"children":1671},{},[1672],{"type":54,"value":1673},"ANTI-PATTERN",{"type":54,"value":1675},": Research says \"use JSON prompts with device specs\" but you write plain prose. This defeats the entire purpose of the research.",{"type":48,"tag":893,"props":1677,"children":1679},{"id":1678},"quality-checklist-run-before-delivering",[1680],{"type":54,"value":1681},"Quality Checklist (run before delivering):",{"type":48,"tag":70,"props":1683,"children":1686},{"className":1684},[1685],"contains-task-list",[1687,1707,1716,1725,1741],{"type":48,"tag":74,"props":1688,"children":1691},{"className":1689},[1690],"task-list-item",[1692,1698,1700,1705],{"type":48,"tag":1693,"props":1694,"children":1697},"input",{"disabled":1695,"type":1696},true,"checkbox",[],{"type":54,"value":1699}," ",{"type":48,"tag":142,"props":1701,"children":1702},{},[1703],{"type":54,"value":1704},"FORMAT MATCHES RESEARCH",{"type":54,"value":1706}," - If research said JSON\u002Fstructured\u002Fetc, prompt IS that format",{"type":48,"tag":74,"props":1708,"children":1710},{"className":1709},[1690],[1711,1714],{"type":48,"tag":1693,"props":1712,"children":1713},{"disabled":1695,"type":1696},[],{"type":54,"value":1715}," Directly addresses what the user said they want to create",{"type":48,"tag":74,"props":1717,"children":1719},{"className":1718},[1690],[1720,1723],{"type":48,"tag":1693,"props":1721,"children":1722},{"disabled":1695,"type":1696},[],{"type":54,"value":1724}," Uses specific patterns\u002Fkeywords discovered in research",{"type":48,"tag":74,"props":1726,"children":1728},{"className":1727},[1690],[1729,1732,1734,1739],{"type":48,"tag":1693,"props":1730,"children":1731},{"disabled":1695,"type":1696},[],{"type":54,"value":1733}," Ready to paste with zero edits (or minimal ",{"type":48,"tag":262,"props":1735,"children":1736},{},[1737],{"type":54,"value":1738},"PLACEHOLDERS",{"type":54,"value":1740}," clearly marked)",{"type":48,"tag":74,"props":1742,"children":1744},{"className":1743},[1690],[1745,1748],{"type":48,"tag":1693,"props":1746,"children":1747},{"disabled":1695,"type":1696},[],{"type":54,"value":1749}," Appropriate length and style for TARGET_TOOL",{"type":48,"tag":893,"props":1751,"children":1753},{"id":1752},"output-format",[1754],{"type":54,"value":1755},"Output Format:",{"type":48,"tag":355,"props":1757,"children":1760},{"className":1758,"code":1759,"language":54},[358],"Here's your prompt for {TARGET_TOOL}:\n\n---\n\n[The actual prompt IN THE FORMAT THE RESEARCH RECOMMENDS]\n\n---\n\nThis uses [brief 1-line explanation of what research insight you applied].\n",[1761],{"type":48,"tag":224,"props":1762,"children":1763},{"__ignoreMap":363},[1764],{"type":54,"value":1759},{"type":48,"tag":377,"props":1766,"children":1767},{},[],{"type":48,"tag":63,"props":1769,"children":1771},{"id":1770},"if-user-asks-for-more-options",[1772],{"type":54,"value":1773},"IF USER ASKS FOR MORE OPTIONS",{"type":48,"tag":57,"props":1775,"children":1776},{},[1777],{"type":54,"value":1778},"Only if they ask for alternatives or more prompts, provide 2-3 variations. Don't dump a prompt pack unless requested.",{"type":48,"tag":377,"props":1780,"children":1781},{},[],{"type":48,"tag":63,"props":1783,"children":1785},{"id":1784},"after-each-prompt-stay-in-expert-mode",[1786],{"type":54,"value":1787},"AFTER EACH PROMPT: Stay in Expert Mode",{"type":48,"tag":57,"props":1789,"children":1790},{},[1791],{"type":54,"value":1792},"After delivering a prompt, offer to write more:",{"type":48,"tag":944,"props":1794,"children":1795},{},[1796],{"type":48,"tag":57,"props":1797,"children":1798},{},[1799],{"type":54,"value":1800},"Want another prompt? Just tell me what you're creating next.",{"type":48,"tag":377,"props":1802,"children":1803},{},[],{"type":48,"tag":63,"props":1805,"children":1807},{"id":1806},"context-memory",[1808],{"type":54,"value":1809},"CONTEXT MEMORY",{"type":48,"tag":57,"props":1811,"children":1812},{},[1813],{"type":54,"value":1814},"For the rest of this conversation, remember:",{"type":48,"tag":70,"props":1816,"children":1817},{},[1818,1827,1837,1847],{"type":48,"tag":74,"props":1819,"children":1820},{},[1821,1825],{"type":48,"tag":142,"props":1822,"children":1823},{},[1824],{"type":54,"value":146},{"type":54,"value":1826},": {topic}",{"type":48,"tag":74,"props":1828,"children":1829},{},[1830,1835],{"type":48,"tag":142,"props":1831,"children":1832},{},[1833],{"type":54,"value":1834},"TARGET_TOOL",{"type":54,"value":1836},": {tool}",{"type":48,"tag":74,"props":1838,"children":1839},{},[1840,1845],{"type":48,"tag":142,"props":1841,"children":1842},{},[1843],{"type":54,"value":1844},"KEY PATTERNS",{"type":54,"value":1846},": {list the top 3-5 patterns you learned}",{"type":48,"tag":74,"props":1848,"children":1849},{},[1850,1855],{"type":48,"tag":142,"props":1851,"children":1852},{},[1853],{"type":54,"value":1854},"RESEARCH FINDINGS",{"type":54,"value":1856},": The key facts and insights from the research",{"type":48,"tag":57,"props":1858,"children":1859},{},[1860],{"type":48,"tag":142,"props":1861,"children":1862},{},[1863],{"type":54,"value":1864},"CRITICAL: After research is complete, you are now an EXPERT on this topic.",{"type":48,"tag":57,"props":1866,"children":1867},{},[1868],{"type":54,"value":1869},"When the user asks follow-up questions:",{"type":48,"tag":70,"props":1871,"children":1872},{},[1873,1883,1893,1903],{"type":48,"tag":74,"props":1874,"children":1875},{},[1876,1881],{"type":48,"tag":142,"props":1877,"children":1878},{},[1879],{"type":54,"value":1880},"DO NOT run new WebSearches",{"type":54,"value":1882}," - you already have the research",{"type":48,"tag":74,"props":1884,"children":1885},{},[1886,1891],{"type":48,"tag":142,"props":1887,"children":1888},{},[1889],{"type":54,"value":1890},"Answer from what you learned",{"type":54,"value":1892}," - cite the Reddit threads, X posts, and web sources",{"type":48,"tag":74,"props":1894,"children":1895},{},[1896,1901],{"type":48,"tag":142,"props":1897,"children":1898},{},[1899],{"type":54,"value":1900},"If they ask a question",{"type":54,"value":1902}," - answer it from your research findings",{"type":48,"tag":74,"props":1904,"children":1905},{},[1906,1911],{"type":48,"tag":142,"props":1907,"children":1908},{},[1909],{"type":54,"value":1910},"If they ask for a prompt",{"type":54,"value":1912}," - write one using your expertise",{"type":48,"tag":57,"props":1914,"children":1915},{},[1916],{"type":54,"value":1917},"Only do new research if the user explicitly asks about a DIFFERENT topic.",{"type":48,"tag":377,"props":1919,"children":1920},{},[],{"type":48,"tag":63,"props":1922,"children":1924},{"id":1923},"output-summary-footer-after-each-prompt",[1925],{"type":54,"value":1926},"Output Summary Footer (After Each Prompt)",{"type":48,"tag":57,"props":1928,"children":1929},{},[1930],{"type":54,"value":1931},"After delivering a prompt, end with:",{"type":48,"tag":355,"props":1933,"children":1936},{"className":1934,"code":1935,"language":54},[358],"---\nExpert in: {TOPIC} for {TARGET_TOOL}\nBased on: {n} Reddit threads ({sum} upvotes) + {n} X posts ({sum} likes) + {n} web pages\n\nWant another prompt? Just tell me what you're creating next.\n",[1937],{"type":48,"tag":224,"props":1938,"children":1939},{"__ignoreMap":363},[1940],{"type":54,"value":1935},{"type":48,"tag":1942,"props":1943,"children":1944},"style",{},[1945],{"type":54,"value":1946},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1948,"total":2051},[1949,1965,1977,1994,2010,2026,2032],{"slug":1950,"name":1950,"fn":1951,"description":1952,"org":1953,"tags":1954,"stars":23,"repoUrl":24,"updatedAt":1964},"ffuf-web-fuzzing","perform web fuzzing with ffuf","Expert guidance for ffuf web fuzzing during authorized penetration testing. Covers directory discovery, subdomain enumeration, parameter fuzzing, authenticated fuzzing with raw requests, auto-calibration, and result analysis. Use when running ffuf scans, analyzing ffuf output, or building fuzzing strategies for web targets.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1955,1958,1961],{"name":1956,"slug":1957,"type":16},"Code Analysis","code-analysis",{"name":1959,"slug":1960,"type":16},"Security","security",{"name":1962,"slug":1963,"type":16},"Testing","testing","2026-07-17T06:05:08.247908",{"slug":1966,"name":1966,"fn":1967,"description":1968,"org":1969,"tags":1970,"stars":23,"repoUrl":24,"updatedAt":1976},"ghidra-headless","reverse engineer binaries with Ghidra","Reverse engineers binaries using Ghidra's headless analyzer. Use when decompiling executables, extracting functions, strings, symbols, or analyzing call graphs from compiled binaries without the Ghidra GUI.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1971,1972,1975],{"name":1956,"slug":1957,"type":16},{"name":1973,"slug":1974,"type":16},"Debugging","debugging",{"name":1959,"slug":1960,"type":16},"2026-07-18T05:47:30.015093",{"slug":1978,"name":1978,"fn":1979,"description":1980,"org":1981,"tags":1982,"stars":23,"repoUrl":24,"updatedAt":1993},"grilling","stress-test plans and decisions","Interviews the user relentlessly about a plan, decision, or idea until every branch of the decision tree is resolved. Use when the user wants to stress-test their thinking, sharpen a plan or design before acting, or uses any 'grill' trigger phrase (e.g. \"grill me on this\").",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1983,1984,1987,1990],{"name":18,"slug":19,"type":16},{"name":1985,"slug":1986,"type":16},"Coaching","coaching",{"name":1988,"slug":1989,"type":16},"Ideation","ideation",{"name":1991,"slug":1992,"type":16},"Strategy","strategy","2026-07-18T05:48:12.46583",{"slug":1995,"name":1995,"fn":1996,"description":1997,"org":1998,"tags":1999,"stars":23,"repoUrl":24,"updatedAt":2009},"handoff","compact conversation for session handoff","Compacts the current conversation into a handoff document so a fresh agent can continue the work in a new session.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2000,2003,2006],{"name":2001,"slug":2002,"type":16},"Agents","agents",{"name":2004,"slug":2005,"type":16},"Context","context",{"name":2007,"slug":2008,"type":16},"Productivity","productivity","2026-07-18T05:47:03.196098",{"slug":2011,"name":2011,"fn":2012,"description":2013,"org":2014,"tags":2015,"stars":23,"repoUrl":24,"updatedAt":2025},"humanizer","edit text to sound human-written","Remove signs of AI-generated writing from text. Use when editing or reviewing\ntext to make it sound more natural and human-written. Based on Wikipedia's\ncomprehensive \"Signs of AI writing\" guide. Detects and fixes patterns including:\ninflated symbolism, promotional language, superficial -ing analyses, vague\nattributions, em dash overuse, rule of three, AI vocabulary words, negative\nparallelisms, and excessive conjunctive phrases. 30c5c8d (Update humanizer plugin to upstream v2.2.0)\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2016,2019,2022],{"name":2017,"slug":2018,"type":16},"Content Creation","content-creation",{"name":2020,"slug":2021,"type":16},"Editing","editing",{"name":2023,"slug":2024,"type":16},"Writing","writing","2026-07-18T05:47:18.1749",{"slug":4,"name":4,"fn":5,"description":6,"org":2027,"tags":2028,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2029,2030,2031],{"name":18,"slug":19,"type":16},{"name":14,"slug":15,"type":16},{"name":21,"slug":22,"type":16},{"slug":2033,"name":2033,"fn":2034,"description":2035,"org":2036,"tags":2037,"stars":23,"repoUrl":24,"updatedAt":2050},"openai-cloudflare-deploy","deploy applications to Cloudflare","Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare. Originally from OpenAI's curated skills catalog.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2038,2041,2044,2047],{"name":2039,"slug":2040,"type":16},"Cloudflare","cloudflare",{"name":2042,"slug":2043,"type":16},"Cloudflare Pages","cloudflare-pages",{"name":2045,"slug":2046,"type":16},"Cloudflare Workers","cloudflare-workers",{"name":2048,"slug":2049,"type":16},"Deployment","deployment","2026-07-17T06:04:46.574433",31,{"items":2053,"total":2201},[2054,2069,2079,2095,2110,2121,2133,2143,2156,2167,2179,2190],{"slug":2055,"name":2055,"fn":2056,"description":2057,"org":2058,"tags":2059,"stars":2066,"repoUrl":2067,"updatedAt":2068},"address-sanitizer","detect memory errors during fuzzing","AddressSanitizer detects memory errors during fuzzing. Use when fuzzing C\u002FC++ code to find buffer overflows and use-after-free bugs.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2060,2063,2064,2065],{"name":2061,"slug":2062,"type":16},"C#","c",{"name":1973,"slug":1974,"type":16},{"name":1959,"slug":1960,"type":16},{"name":1962,"slug":1963,"type":16},6139,"https:\u002F\u002Fgithub.com\u002Ftrailofbits\u002Fskills","2026-07-17T06:05:14.925095",{"slug":2070,"name":2070,"fn":2071,"description":2072,"org":2073,"tags":2074,"stars":2066,"repoUrl":2067,"updatedAt":2078},"aflpp","perform multi-core fuzzing of C\u002FC++ projects","AFL++ is a fork of AFL with better fuzzing performance and advanced features. Use for multi-core fuzzing of C\u002FC++ projects.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2075,2076,2077],{"name":2061,"slug":2062,"type":16},{"name":1959,"slug":1960,"type":16},{"name":1962,"slug":1963,"type":16},"2026-07-17T06:05:12.433192",{"slug":2080,"name":2080,"fn":2081,"description":2082,"org":2083,"tags":2084,"stars":2066,"repoUrl":2067,"updatedAt":2094},"agentic-actions-auditor","audit GitHub Actions for security vulnerabilities","Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI\u002FCD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI\u002FCD pipeline security for prompt injection risks, or evaluating agentic action configurations.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2085,2086,2089,2090,2093],{"name":2001,"slug":2002,"type":16},{"name":2087,"slug":2088,"type":16},"CI\u002FCD","ci-cd",{"name":1956,"slug":1957,"type":16},{"name":2091,"slug":2092,"type":16},"GitHub Actions","github-actions",{"name":1959,"slug":1960,"type":16},"2026-07-18T05:47:48.564744",{"slug":2096,"name":2096,"fn":2097,"description":2098,"org":2099,"tags":2100,"stars":2066,"repoUrl":2067,"updatedAt":2109},"algorand-vulnerability-scanner","scan Algorand smart contracts for vulnerabilities","Scans Algorand smart contracts for 11 common vulnerabilities including rekeying attacks, unchecked transaction fees, missing field validations, and access control issues. Use when auditing Algorand projects (TEAL\u002FPyTeal).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2101,2104,2105,2106],{"name":2102,"slug":2103,"type":16},"Audit","audit",{"name":1956,"slug":1957,"type":16},{"name":1959,"slug":1960,"type":16},{"name":2107,"slug":2108,"type":16},"Smart Contracts","smart-contracts","2026-07-18T05:47:43.989063",{"slug":2111,"name":2111,"fn":2112,"description":2113,"org":2114,"tags":2115,"stars":2066,"repoUrl":2067,"updatedAt":2120},"ask-questions-if-underspecified","clarify requirements before implementation","Clarify requirements before implementing. Use when serious doubts arise.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2116,2119],{"name":2117,"slug":2118,"type":16},"Engineering","engineering",{"name":2007,"slug":2008,"type":16},"2026-07-17T06:05:33.543262",{"slug":2122,"name":2122,"fn":2123,"description":2124,"org":2125,"tags":2126,"stars":2066,"repoUrl":2067,"updatedAt":2132},"atheris","fuzz Python code with Atheris","Atheris is a coverage-guided Python fuzzer based on libFuzzer. Use for fuzzing pure Python code and Python C extensions.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2127,2130,2131],{"name":2128,"slug":2129,"type":16},"Python","python",{"name":1959,"slug":1960,"type":16},{"name":1962,"slug":1963,"type":16},"2026-07-17T06:05:14.575191",{"slug":2134,"name":2134,"fn":2135,"description":2136,"org":2137,"tags":2138,"stars":2066,"repoUrl":2067,"updatedAt":2142},"audit-augmentation","augment code graphs with audit findings","Augments Trailmark code graphs with external audit findings from SARIF static analysis results, weAudit annotation files, and version-gated Trailmark 0.4.x binary-analysis graph exports. Maps findings to graph nodes by file and line overlap, creates severity-based subgraphs, and enables cross-referencing findings with pre-analysis data (blast radius, taint, etc.). Use when projecting SARIF results onto a code graph, overlaying weAudit annotations, importing binary graph findings, cross-referencing Semgrep, CodeQL, or binary-analysis findings with call graph data, or visualizing audit findings in the context of code structure.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2139,2140,2141],{"name":2102,"slug":2103,"type":16},{"name":1956,"slug":1957,"type":16},{"name":1959,"slug":1960,"type":16},"2026-08-01T05:44:54.920542",{"slug":2144,"name":2144,"fn":2145,"description":2146,"org":2147,"tags":2148,"stars":2066,"repoUrl":2067,"updatedAt":2155},"audit-context-building","build architectural context for code analysis","Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2149,2152,2153,2154],{"name":2150,"slug":2151,"type":16},"Architecture","architecture",{"name":2102,"slug":2103,"type":16},{"name":1956,"slug":1957,"type":16},{"name":2117,"slug":2118,"type":16},"2026-07-18T05:47:40.122449",{"slug":2157,"name":2157,"fn":2158,"description":2159,"org":2160,"tags":2161,"stars":2066,"repoUrl":2067,"updatedAt":2166},"audit-prep-assistant","prepare codebases for security audits","Prepares codebases for security review using Trail of Bits' checklist. Helps set review goals, runs static analysis tools, increases test coverage, removes dead code, ensures accessibility, and generates documentation (flowcharts, user stories, inline comments).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2162,2163,2164,2165],{"name":2102,"slug":2103,"type":16},{"name":1956,"slug":1957,"type":16},{"name":2117,"slug":2118,"type":16},{"name":1959,"slug":1960,"type":16},"2026-07-18T05:47:39.210985",{"slug":2168,"name":2168,"fn":2169,"description":2170,"org":2171,"tags":2172,"stars":2066,"repoUrl":2067,"updatedAt":2178},"burpsuite-project-parser","parse Burp Suite project files","Searches and explores Burp Suite project files (.burp) from the command line. Use when searching response headers or bodies with regex patterns, extracting security audit findings, dumping proxy history or site map data, or analyzing HTTP traffic captured in a Burp project.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2173,2174,2177],{"name":2102,"slug":2103,"type":16},{"name":2175,"slug":2176,"type":16},"CLI","cli",{"name":1959,"slug":1960,"type":16},"2026-07-17T06:05:33.198077",{"slug":2180,"name":2180,"fn":2181,"description":2182,"org":2183,"tags":2184,"stars":2066,"repoUrl":2067,"updatedAt":2189},"c-review","audit C and C++ code","Performs comprehensive C\u002FC++ security review for memory corruption, integer overflows, race conditions, and platform-specific vulnerabilities. Use when auditing native C\u002FC++ applications, reviewing daemons or services for memory safety, or hunting integer overflow \u002F use-after-free \u002F race conditions in userspace code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2185,2186,2187,2188],{"name":2102,"slug":2103,"type":16},{"name":2061,"slug":2062,"type":16},{"name":1956,"slug":1957,"type":16},{"name":1959,"slug":1960,"type":16},"2026-07-17T06:05:11.333374",{"slug":2191,"name":2191,"fn":2192,"description":2193,"org":2194,"tags":2195,"stars":2066,"repoUrl":2067,"updatedAt":2200},"cairo-vulnerability-scanner","scan Cairo and StarkNet contracts for vulnerabilities","Scans Cairo\u002FStarkNet smart contracts for 6 critical vulnerabilities including felt252 arithmetic overflow, L1-L2 messaging issues, address conversion problems, and signature replay. Use when auditing StarkNet projects.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[2196,2197,2198,2199],{"name":2102,"slug":2103,"type":16},{"name":1956,"slug":1957,"type":16},{"name":1959,"slug":1960,"type":16},{"name":2107,"slug":2108,"type":16},"2026-07-18T05:47:42.84568",111]